Changing face of market research. Rise of Data Science.

1. Vanishing pie of
Market Research
&
The Rise of
Data Science
1
DATE: 21st August 2018

2. About MRSI
• A unique not-for-profit association of providers and buyers of
research and insights
• Established in 1988 to:
– Create awareness of the industry among public at large as well as
government
– Establish and promote professional standards
– Provide a platform for professionals to engage and showcase their
work and collaborate on common issues
For more details, visit www.mrsi.in

3. Session Host:
Sandeep Arora
Vice President, MRSI
Introduction
Context

4. Speaker Today:
Preriit Souda
Director, PSA Consultants Ltd
London, UK
Preriit is a Director at PSA Consultants based in London, UK.
Preriit’s key focus is to help organisations answer difficult strategic questions by unraveling
explicit and implicit human expression through mining social media & digital data. His
work has helped develop new products and track brand reputation using social & digital
data alongside more traditional market research approaches such as Survey, focus groups,
IOT, Google search data, weather, geospatial data, CRM and mobile data.

5. Coverage:
1. The Context - Changes in Market Research
2. Paper 1: Can Chairs Talk (Best Paper ESOMAR Global Congress ’17- Amsterdam, NL)
3. Paper 2: Knitting data for brocade of insights (Winning paper ARF Audience X Science
’18, New Jersey, US – abridged version)

6. Changes in
Market Research
6

7. Changes in 4 dimensions
Research
Suppliers
Research
Users
Eco
System Methods

8. Changes in MRX: Research Users
● Struggling to show value (of research) internally
● Increasing need for integration between research, strategy, marketing etc
● Creation of internal capabilities
● Zero based budgeting
● For long tail clients (SMEs), research is a luxury with no clear returns

9. Changes in MRX: Research Suppliers
Consulting
players
Traditional
research players
[shrinking]
Technology enabled
players

10. Changes in MRX: Research Suppliers
● Traditional research will NOT die but will not live either.
● Consolidations, Commoditization, stagnancy in employee remunerations and
headcount reduction
● Technology enabled players are threatening traditional players while AdTech,
MarTech players are extending into insights
● Market is ripe for the taking
● Advice -> Adapt or die

11. Changes in MRX: Ecosystem
● Survey response rates are falling down and will continue to
● Survey or Qual are no longer the only ways to do market research
● Privacy and data usage is a growing public concern
● Overhyping of capabilities of AI poses a challenge

12. Changes in MRX: Methods
● Data Science, AI, Analytics becoming more and more important
● Growing number of disparate, disjoint, fast moving data sources require
new & different ways of thinking
● Need for insight translators is growing
● Training for cross-usage of techniques from Data Science, Traditional
analytics, Qualitative & Quantitative methods & other domain specific
knowledge is required

13. Can Chairs talk?
1
3

14. Arper (an award-winning Italian design
company) wanted to complement their
five year strategic plan with
an insightful understanding of the
amount of interest in the brand through
digital media in key markets.
The challenge
preriit2131

15. Text mine Insights
Extract the data
@preriit2131 #IIEX
Seemed like a regular project!
#1
Teach machine about the sector to text
mine
Teach ourselves about the sector

16. Problem (missed a large portion of data)
preriit2131

17. Solution
Extracting images from existing data
(using meta data):
In total, around 15 GB of images
were extracted
preriit2131

18. Solution
Image tagging
Broad category of tags:
• Types of furniture
• Brand, logos and collections
• Colours used in the image
• Colour distribution
• Type of background,
• Context
• People, etc.
preriit2131

19. Image crawling:
Tagged images were used as seed images for crawler (offered by rezf/shareiq)
Solution
preriit2131

20. Analysis: Combining text mining and image analysis
Brand imagery
Brand 2
Brand 3
Brand 5
Brand 4
Brand imagery 1
Brand imagery 2
Brand imagery 4
Brand imagery 3
Sub brand imagery 1
Brand imagery 5
Functional attribution 1
Functional attribution 2
Brand imagery influenced
by geographic connotation
Brand imagery tied to other
non-designer brands
Brand imagery influenced
by geographic connotation
Brand 1Brand 1
Brand 2
Brand 3
Brand 4
Brand 5
Brand imagery 1
Brand imagery 2
Brand imagery 3
Brand imagery 4
Sub brand imagery 1
Brand imagery 5
Functional attribution 1
Functional attribution 2
Brand imagery influenced
by geographic connotation
Brand imagery tied to other
non-designer brands
Brand imagery influenced
by geographic connotation
preriit2131

21. Analysis: Overall metrics
1 2 3 4 5
x%
Comparative rank
Text only
Tonality
Images only
preriit2131

22. • While being Italian, Arper is perceived as
an international brand with creative traits.
• People talk about a design brand
because of its collections linked to
cultural projects, so cultural investments
can make a difference in brand
perception.
• Arper’s core audience is made up of
architects, but this audience can often
derive inspiration from art experts.
Strategic insights (abridged)
preriit2131

23. Knitting data for
Brocade of insights
2
3

24. Data Linkage Framework
Social &
Digital
data with all
its available
Meta data
Text Mined Attributes
Image Mined Attributes
Demographic Attributes
Locational Attributes
Weather Attributes
Travel (Footfall, Car traffic etc) data
Telecom usage data
App usage data
CRM data
Advert Banner viewing & expense data
Operational (egg: train delays etc.) data
TV ratings data or Set Top box viewing data
Geospatial sales data
Geospatial store presence data
Music Meta info
Store/ Restaurant Reviews data
Web Analytics data
Search data
Immigration data
Traditional Research data
Etc.
preriit2131

25. Superimposing Survey created segments
on social and digital data
Problem:
preriit2131

26. Togetherness moment
Aficionado Gratification
Inspiring occasions Well being
Diurnal rituals
preriit2131

27. Togetherness OccasionsTogetherness moment
With whom
When
Where
With what
Derived happiness
Emotional connect
Celebrations
preriit2131

28. Lat: 51.5074° N
Long: 0.1278° W
Cafeteria Brand X near to a
Public park
Temperature: -3* C
Date: 18 Dec (8:30 am)
Male, Irish ancestry, Architect into
baseball
Text data
Location data linked with geospatial info
Weather data
Meta data linked with other info
example
Life without friends – hell
#together #coffee
preriit2131

29. v/s
Helped us classify 36% extra data making
Our superimposition better and more robust
Data, Meta data + OtherData
preriit2131

30. Closing Remarks
preriit2131
• Its no more the same world as seen with the two cases. Such examples are going to increase not
decrease; go from novelty to mainstream in coming 4-8 years
• For Research Users: Integrate internal and external data, show measurable results and don’t remain
limited only to market research department- expand horizons of your work and also your skills
• For Research suppliers: Technology is making a major impact on traditional research players which they
seem to be unable to fight back- but do they really need to fight or adapt?
• While Privacy and data usage are concerns, AI and Data Science will continue to grow - like it or not
• MR practitioners should embrace rather than oppose the new methods: learn new skills by use of
MOOCs for data science and then adapt to your context. Additionally, ESOMAR, MRSI etc need to have
workshops &/or courses on data science & market research.

31. preriit2131
Math, Statistics,
new methods &
thinking
Domain knowledge
: Marketing, Advertising
& core ideas of market
research
: basics of client’s sector
Human Psychology,
Social Science etc.
New analytical
tools + basics of
computer
science
Inward led changes/upgrades - Individual level
Knowledge
of new data
Ecosystem
Creative use
Of data

32. preriit2131
New Organizational
Structures:
Data Science + IT +
Translators & Integrators
Culture Change:
Acceptance of the new world of disparate disjoint
data & its possibilities
Inward led changes- Institutional level requirements
Patience
+
Risk appetite ?
Economics:
- Multiple non research data
providers
- Costing methods change:
interview led to data, time &
outcome led

33. Questions?
Sandeep Saxena
Director General, MRSI
📩 sandeep.saxena@mrsi.in
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